Currently, numerous population pharmacokinetic (Pop PK) models for methotrexate (MTX) have been published, estimating its pharmacokinetic parameters and variability. However, it is unclear whether the accuracy of these models is sufficient for clinical application. The aim of this study is to evaluate published models and assess their predictive performance according to the standards of scientific research. A total of 237 samples from 74 adult patients who underwent high‐dose methotrexate (HDMTX) treatment at Shanghai Changzheng Hospital were collected. The NONMEM software package was used to perform external evaluation for each model, including prediction‐based diagnosis, simulation‐based diagnosis, and Bayesian forecasting. The Simulation‐based diagnosis includes normalized prediction distribution error (NPDE) and visual predictive check (VPC). Following screening, seven candidate models suitable for external validation were identified for comparison. However, none of these models exhibited excellent predictive performance. Bayesian simulation results indicated that the prediction precision and accuracy of all models significantly improved when incorporating prior concentration information. Published Pop PK models for MTX exhibit significant differences in their predictive performance, and none of the models were able to accurately predict MTX concentrations in our dataset. Therefore, before adopting any model in clinical practice, extensive evaluation should be conducted.This article is protected by copyright. All rights reserved